import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

import pywt

df = pd.read_csv('z_rate.csv')

x = df.index
y = df['z_avgRate']

# perform wavelet decomposition
coeffs = pywt.wavedec(y, 'sym5', mode='symmetric')

# zero out last 5 detail coefficents
for i in range(5):
    coeffs[i+5] = np.zeros(coeffs[i+5].shape)

# reconstruct wavelet
y_rec = pywt.waverec(coeffs, 'sym5', mode='symmetric')[1:]

# plot result
plt.figure(figsize=(18,6))
plt.plot(x, y)
plt.plot(x, y_rec)
plt.legend(['original', 'wavelet-based smoothing'])
plt.xlabel('time index')
plt.show()